Biomarker Change Indicator for Behavioral Health

ABSTRACT

Embodiments describing an approach for detecting user biomarker identifier changes based on audio preferences and generating biometric alerts based on the detected biomarker identifier changes. Receiving a user&#39;s current audio preferences. Retrieving the user&#39;s historic audio preferences and biometric data associated with the user&#39;s historic audio preferences. Analyzing the user&#39;s current audio preferences based on the user&#39;s historic audio preferences and the biometric data associated with the historic audio preferences. Creating a user biometric profile based on analyzing the user&#39;s current audio preferences, the user&#39;s historic audio preferences and the biometric data associated with the user&#39;s historic audio preferences; and outputting the user biometric profile.

BACKGROUND OF THE INVENTION

The present invention relates generally to the field of biometricmonitoring, and more particularly to measure, analyze, monitor, and/orrecord biometric and/or biomarker changes in a user.

Many people listen to music while they are working, exercising, driving,doing homework etc. Having the right music playing during a particularactivity is often key to the user's happiness and success for thatactivity, and can be used to monitor a user's health by monitoringbiometric identifiers. Biometric identifiers are the distinctive,measurable characteristics used to label and describe individuals.Biometric identifiers (i.e., biometric data) are often categorized asphysiological versus behavioral characteristics. Physiologicalcharacteristics are related to the shape of the body. Examples include,but are not limited to fingerprint, palm veins, face recognition, DNA,palm print, hand geometry, iris recognition, retina and odor/scent.Behavioral characteristics are related to the pattern of behavior of aperson, including but not limited to typing rhythm, gait, and voice.

These biometric identifiers are often used as biomarkers indicative of apresence of disease/infection or specific environmental exposure.Biometric identifiers are a valuable indicator for health issues,including mental health issues, yet many individuals do not usebiometric capable devices to record biometric feed/data. Predictions for2017 include an estimated 200 million biometric capable devices will besold. Creating a clear need to passively acquire biometric identifiersto capture key biometric data and change healthcare monitoring, and needto better detect biomarker changes in order to intervene with behavioraland/or overall health.

SUMMARY

Embodiments of the present invention disclose a method, a computerprogram product, and a system for biomarker identifier changes. A methodfor detecting user biomarker identifier changes based on audiopreferences and generating biometric alerts based on the detectedbiomarker identifier changes, the method includes receiving, by one ormore processors, a user's current audio preferences. Retrieving, by theone or more processors, the user's historic audio preferences andbiometric data associated with the user's historic audio preferences.Analyzing, by the one or more processors, the user's current audiopreferences based on the user's historic audio preferences and thebiometric data associated with the historic audio preferences. Creating,by the one or more processors, a user biometric profile based onanalyzing the user's current audio preferences, the user's historicaudio preferences and the biometric data associated with the user'shistoric audio preferences, and outputting, by the one or moreprocessors, the user biometric profile.

A computer program product for detecting user biomarker identifierchanges based on audio preferences and generating biometric alerts basedon the detected biomarker identifier changes, the computer programproduct includes one or more computer readable storage devices andprogram instructions stored on the one or more computer readable storagedevices, the stored program instructions comprising, programinstructions to receive a user's current audio preferences. Programinstructions to retrieve the user's historic audio preferences andbiometric data associated with the user's historic audio preferences.Program instructions to analyze the user's current audio preferencesbased on the user's historic audio preferences and the biometric dataassociated with the historic audio preferences. Program instructions tocreate a user biometric profile based on analyzing the user's currentaudio preferences, the user's historic audio preferences and thebiometric data associated with the user's historic audio preferences,and program instructions to output the user biometric profile.

A computer system for detecting user biomarker identifier changes basedon audio preferences and generating biometric alerts based on thedetected biomarker identifier changes, the computer system includes oneor more computer processors, one or more computer readable storagedevices, program instructions stored on the one or more computerreadable storage devices for execution by at least one of the one ormore computer processors, the stored program instructions comprising,program instructions to receive a user's current audio preferences.Program instructions to retrieve the user's historic audio preferencesand biometric data associated with the user's historic audiopreferences. Program instructions to analyze the user's current audiopreferences based on the user's historic audio preferences and thebiometric data associated with the historic audio preferences. Programinstructions to create a user biometric profile based on analyzing theuser's current audio preferences, the user's historic audio preferencesand the biometric data associated with the user's historic audiopreferences, and program instructions to output the user biometricprofile.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a functional block diagram illustrating a distributed dataprocessing environment, in accordance with an embodiment of the presentinvention;

FIG. 2 illustrates operational steps of biomarker identifier component,on a server computer within the distributed data processing environmentof FIG. 1, in accordance with an embodiment of the present invention;

FIG. 3 illustrates operational steps of biomarker identifier component,on a server computer within the distributed data processing environmentof FIG. 1, in accordance with an embodiment of the present invention;and

FIG. 4 depicts a block diagram of components of the server computerexecuting the calibration component within the distributed dataprocessing environment of FIG. 1, in accordance with an embodiment ofthe present invention.

DETAILED DESCRIPTION

Embodiments of the current invention leverages the music played by thedevice currently to determine the user's biometric information.Embodiments of the current invention can source user's biometricinformation (approximate or exact or relative affect) from music thatthe user played or is currently playing, based on previously sourcedbiometric information from biometric capable devices while a user playsmusic. For example, a smart watch that records a user's biometricidentifiers and/or vitals while the user exercises. The music monitoredcan be current music playing or historical music playing to cover a goodrange of user's biometric information for further interesting analysisof user's biometric information. Embodiments of the present inventioncan also focus on segment of music rather than an entire musical track.Embodiments of the current invention normalize on music satisfaction(e.g. a user fast forwarded so they must be annoyed by music more thanamplifying or reflecting the music's pattern). Embodiments of thecurrent invention can isolate the music based on region or demographicbackground (i.e., age, gender, region, etc.) or medical background. Thebiometric data can be a relative indicator versus a real indicator.Embodiments of the current invention improve the field of user biometricand user biomarker monitoring, analysis, and recording.

Embodiments of the present invention are capable of recording and/orcollecting user biometric information without any additional action fromthe user. Embodiments of the present invention improve the art ofbiometric data by enabling the collection of biometric information fromthe user when the user doesn't have a biometric capable device.Additionally, embodiments of the present invention can understand user'sbiometric information to better serve the user, and understand user'schange of biometric information and leverage that information to betterserve the user.

Biometric identifiers are then distinctive, measurable characteristicsused to label and describe individuals. Biometric identifiers are oftencategorized as physiological versus behavioral characteristics.Physiological characteristics are related to the shape of the body.Examples include, but are not limited to fingerprint, palm veins, facerecognition, DNA, palm print, hand geometry, iris recognition, retinaand odor/scent. Behavioral characteristics are related to the pattern ofbehavior of a person, including but not limited to typing rhythm, gait,and voice. Biometric identifiers can often be used as biomarkersindicative of a presence of disease/infection or specific environmentalexposure.

It should be noted that biometric identifier(s) and/or biometric dataare interchangeable and synonymous with one another. Additionally, itshould be noted that biometric identifier(s) and/or data areinterchangeable and/or synonymous with biomarker identifier(s) and/orbiomarker data throughout the entire specification.

Implementation of embodiments of the invention may take a variety offorms, and exemplary implementation details are discussed subsequentlywith reference to the Figures.

The programs described herein are identified based upon the applicationfor which they are implemented in a specific embodiment of theinvention. However, it should be appreciated that any particular programnomenclature herein is used merely for convenience, and thus theinvention should not be limited to use solely in any specificapplication identified and/or implied by such nomenclature.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be any tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It can be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, a special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, a segment, or aportion of instructions, which comprises one or more executableinstructions for implementing the specified logical function(s). In somealternative implementations, the functions noted in the blocks may occurout of the order noted in the Figures. For example, two blocks shown insuccession may, in fact, be executed substantially concurrently, or theblocks may sometimes be executed in the reverse order, depending uponthe functionality involved. It can also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations can be apparent to those of ordinary skillin the art without departing from the scope and spirit of the invention.The terminology used herein was chosen to best explain the principles ofthe embodiment, the practical application or technical improvement overtechnologies found in the marketplace, or to enable others of ordinaryskill in the art to understand the embodiments disclosed herein.

FIG. 1 is a functional block diagram illustrating a distributed dataprocessing environment, generally designated 100, in accordance with oneembodiment of the present invention. The term “distributed” as used inthis specification describes a computer system that includes multiple,physically distinct devices that operate together as a single computersystem. FIG. 1 provides only an illustration of one implementation anddoes not imply any limitations with regard to the environments in whichdifferent embodiments may be implemented. Many modifications to thedepicted environment may be made by those skilled in the art withoutdeparting from the scope of the invention as recited by the claims.

Distributed data processing environment 100 includes mobile device 110,server computer 120, interconnected over network 130. Network 130 canbe, for example, a telecommunications network, a local area network(LAN), a wide area network (WAN), such as the Internet, or a combinationof the three, and can include wired, wireless, or fiber opticconnections. Network 130 can include one or more wired and/or wirelessnetworks that are capable of receiving and transmitting data, voice,and/or video signals, including multimedia signals that include voice,data, and video information. In general, network 130 can be anycombination of connections and protocols that will supportcommunications between mobile device 110 and server computer 120, andother computing devices (not shown in FIG. 1) within distributed dataprocessing environment 100.

In various embodiments, mobile device 110 can be, but is not limited to,a standalone device, a server, a laptop computer, a tablet computer, anetbook computer, a personal computer (PC), a smart phone, a desktopcomputer, a smart television, a smart watch, a wearable fitness device,a biometric device, and/or any programmable electronic computing devicecapable of communicating with various components and devices withindistributed data processing environment 100, via network 130 or anycombination therein. In general, mobile device 110 are representative ofany programmable mobile device or a combination of programmable mobiledevices capable of executing machine-readable program instructions andcommunicating with users of other mobile devices via network 130 and/orcapable of executing machine-readable program instructions andcommunicating with server computer 120. In other embodiments, mobiledevice 110 can represent any programmable electronic computing device orcombination of programmable electronic computing devices capable ofexecuting machine readable program instructions, manipulating executablemachine readable instructions, and communicating with server computer120 and other computing devices (not shown) within distributed dataprocessing environment 100 via a network, such as network 130. Mobiledevice 110 includes an instance of user interface 106. Mobile device 110and user interface 106 allow a user to interact with biomarkeridentifier component (BIC) 122 in various ways, such as sending programinstructions, receiving messages, sending data, inputting data, editingdata, correcting data and/or receiving data.

User interface (UI) 106 provides an interface to biomarker identifiercomponent 122 on server computer 120 for a user of mobile device 110. Inone embodiment, UI 106 can be a graphical user interface (GUI) or a webuser interface (WUI) and can display text, documents, web browserwindows, user options, application interfaces, and instructions foroperation, and include the information (such as graphic, text, andsound) that a program presents to a user and the control sequences theuser employs to control the program. In another embodiment, UI 106 canalso be mobile application software that provides an interface between auser of mobile device 110 and server computer 120. Mobile applicationsoftware, or an “app,” is a computer program designed to run on smartphones, tablet computers and other mobile devices. In an embodiment, UI106 enables the user of mobile device 110 to send data, input data, editdata, correct data and/or receive data. In various embodiments, UI 106can enable the user to upload/enter user biomarker and/or user biometricidentifiers to biomarker identifier component 122 for analysis and/orcognitive learning.

Server computer 120 can be a standalone computing device, a managementserver, a web server, a mobile computing device, or any other electronicdevice or computing system capable of receiving, sending, and processingdata. In other embodiments, server computer 120 can represent a servercomputing system utilizing multiple computers as a server system, suchas in a cloud computing environment. In another embodiment, servercomputer 120 can be a laptop computer, a tablet computer, a netbookcomputer, a personal computer (PC), a desktop computer, a personaldigital assistant (PDA), a smart phone, or any other programmableelectronic device capable of communicating with mobile device 110 andother computing devices (not shown) within distributed data processingenvironment 100 via network 130. In another embodiment, server computer120 represents a computing system utilizing clustered computers andcomponents (e.g., database server computers, application servercomputers, etc.) that act as a single pool of seamless resources whenaccessed within distributed data processing environment 100. Servercomputer 120 can include biomarker identifier component 122 and sharedstorage 124. Server computer 120 can include internal and externalhardware components, as depicted, and described in further detail withrespect to FIG. 4.

Shared storage 124 and local storage 108 can be a data repository and/ora database that can be written to and/or read by one or a combination ofbiomarker identifier component 122, server computer 120 and/or computingdevices 110. In the depicted embodiment, shared storage 124 resides onserver computer 120. In another embodiment, shared storage 124 canreside elsewhere within distributed data processing environment 100provided coverage assessment program 110 has access to shared storage124. A database is an organized collection of data. Shared storage 124and/or local storage 108 can be implemented with any type of storagedevice capable of storing data and configuration files that can beaccessed and utilized by server computer 120, such as a database server,a hard disk drive, or a flash memory. In other embodiments, sharedstorage 124 and/or local storage can be hard drives, memory cards,computer output to laser disc (cold storage), and/or any form of datastorage known in the art. In various embodiments, biomarker identifiercomponent 122 can store and/or retrieve data from shared storage 124and/or local storage 108. For example, biomarker identifier component122 stores biometric data to shared storage 124 to be retrieved laterand used as a reference and/or element of analysis.

In various embodiments, biomarker identifier component 122 can create auser profile and store the user profile data on local storage 122 and/orshared storage 124. Additionally, in various embodiments, biomarkeridentifier component 122 can have cognitive capabilities and learn frompreviously save/stored data, and/or any data that biomarker identifiercomponent 122 has interacted with previously. For example, retrievingand analyze a user's previously documented to determine the mostefficient method of repair. Biometric identifiers and/or biometric datacan be, but is not limited to, age, gender, heritage, language, medicalhistory, height, weight, body mass index (BMI) geographical region,nationality, general medical knowledge/information, blood pressure,heart rate, calories burned and/or calories consumed, steps taken, mileswalked, steps ran/jogged, distance ran, steps taken, oxygen levels,glucose level, blood pH level, salinity of user perspiration,perspiration level, behavioral health history, dopamine level, brainactivity, and/or body temperature. In some embodiments, biometric datacan include user data/personal data. Biomarker identifier can be, but isnot limited to, current mood, historic mood, type of music associatedwith mood, behavior (music selection, skipping songs, fast-forwarding,repeating songs, intensity of a workout, etc.), music selection (e.g.,music selection, genera of music, tone, rhythm, pitch, volume, etc.),facial expressions, and/or user biometric identifiers responding tomusic selection (change in heart rate, change in pulse, amount ofperspiration, change in breaths per minute, change in dopamine level,etc.).

In the exemplary embodiment, biomarker identifier component 122 ishoused on server computer 120; however, in other embodiments, biomarkeridentifier component 122 can be housed on mobile device 110, and/or acomputing device and/or server computer not depicted in FIG. 1. Invarious embodiments, biomarker identifier component 122 can link to abiometric capable device and monitor and/or record (e.g., a recordingmodule) biometric data. For example, a user wears the biometric capabledevice (i.e., Smart Watch) and plays music, biomarker identifiercomponent 122 collects user's location/region the user's age, gender andbiometric information, Music played with satisfaction, and time window(e.g., a predetermined time interval, range, and/or duration of a songplayed).

In various embodiments, biomarker identifier component 122 can utilizethe biometric data and/or biomarker identities collected/recorded byand/or entered into a biometric capable device, biometric capable mobileapplication, biometric data website, and/or mobile music application tocreate a user biometric profile. For example, linking to a mobile musicapplication and/or a fitness application, receiving the user's currentaudio preference, in this particular example it's Hip-hop, thenretrieving and comparing the user's historic audio preferences andhistoric biometric data to the user's current audio preferences andaudio preferences. Furthermore, in this particular example, biomarkeridentifier component 122 creates a user biometric profile based on theanalysis of the user's current and historic audio preferences andbiometric data, and outputs the profile to the user and/or medicalprofessional. In various embodiments, biomarker identifier component 122can have a learning phase, in which biomarker identifier component 122monitors and/or records a user's biometric data, biomarker identifiers,and/or audio preferences. Audio preferences can be, but are not limitedto, genre, music artist, lyrics, volume music is played, frequency ofsongs played (e.g., frequently played songs), custom playlists, savedsongs, liked songs, disliked songs, and/or songs skipped. In variousembodiments, biomarker identifier component 122 can retrieve audiopreferences form a music application (e.g., mobile music application).In various embodiments, audio preferences can comprise music attributes(e.g., subjective music attributes and/or objective music attributes).

In various embodiments, biomarker identifier component 122 can, crowdsource biometric data, behavioral data, and/or biomarker identifiers andrecord them accordingly. In various embodiments, biomarker identifiercomponent 122 can integrate with a cloud based cognitive system,artificial intelligent computer system, and/or management system. Invarious embodiments, biomarker identifier component 122 can utilize thelocation information from mobile device 110 (e.g., global positioningsystem (gps) tracking and/or location information). Additionally, invarious embodiments, biomarker identifier component 122 can access auser's mobile applications and/or website profile and retrieve biometricdata. For example, a user's age, gender, location, location history,preferences, and/or occupation from a music streaming website and/ormobile application, and/or from social media websites and/or mobileapplications.

In various embodiments, biomarker identifier component 122 can use acloud based service to collect biometric data, behavioral data, and/orbiomarker identifiers and cognitively learn a user's musicalpreferences, behavioral data (e.g., how certain songs effect a user'smood, and/or how the user's mood effects song selection/song choice).For example, monitoring and recording if the user has fast forwarded themusic versus if the user has fully listened to the music or evenrepetitively played the music or “liked” the music. In variousembodiments, music played with satisfaction can be determined bymonitoring and/or recording user behavior and audio preference.

In various embodiments, biomarker identifier component 122 can collectbiometric data and/or biomarker identifiers when a user is not wearing abiometric capable device. For example, a user listening to music in acar while driving, via Bluetooth connection to the user's smartphone,biomarker identifier component 122 can collect the user'slocation/region, age, gender, music played with satisfaction (e.g.,duration of each song played, type of songs skipped, music genre, etc.),and time window. In various embodiments, biomarker identifier component122 examines the music played during the time the user isn't wearing abiometric capable device and determines the associated biometricinformation by sourcing information/data from the recorded/historic dataof when the user was wearing a biometric capable device. In variousembodiments, when there is enough data collected from when a user iswearing a biometric device, the accuracy of the sourcing can be furtherimproved by matching user's gender, age window, and/or evenlocation/region.

In various embodiments, biomarker identifier component 122 can identifybiomarker change indicators for behavioral health, by: monitoring and/orrecording music choices, extracting the attributes of the music choices,model the attributes of the music choices against historic biomarkerdata, and alert a user to one or more changes to the biomarker changeindicators and/or biometric data. In various embodiments, biomarkeridentifier component 122 can split the music selection into segments(e.g., 1 sec, 10 sec), key changes, time changes, and/orlatent/background audio and accumulate a score over a predeterminedtime-period/interval before alerting a user and/or medical professional.In various embodiments, the accumulated score can be a predeterminedthreshold set by the user, legal guardian, and/or medical professional.In various embodiments, the music segments can be predetermined. In someembodiments, the alert can in the form of a text, a phone call, anemail, a social media post, a push notification, shutting down themobile music application, playing a voice recording, one or morevibrations, one or more sounds, and/or any other form of notificationmethods known in the art. In other embodiments, biomarker identifiercomponent 122 can output one or more alerts. In some embodiments, thealert system can be incremental and increase with intensity based on apredetermined threshold.

In various embodiments, the accumulated score based on current andhistoric user biometric data and/or biomarker identifiers can be used todevelop cohort models as indicators of behavioral health, use the alertas an approximate, exact or relative effect, and/or isolate the musicbased on region or demographic background (e.g., age, gender, region) ormedical background. In various embodiments, biomarker identifiercomponent 122 monitors, records, and/or analyzes the quality of music byparsing the music into subjective music attributes and objective musicattributes, in which the subjective music attributes and objective musicattributes can be used for analysis. Subjective music attributescomprises: Tonal character (usually pitched), noisy, with or withoutsome tonal character, including rustle noise, coloration, beginning,ending, coloration glide or formant glide, micro-intonation,microtonality, vibrato, tremolo, attack, final sound, and/or any othersubjective music attribute known in the art. Objective music attributescomprise: periodic sound, noise (e.g., random pulses characterized bythe rustle time, the mean interval between pulses), spectral envelope,physical rise and decay time, change of spectral envelope, change infrequency (e.g., a predetermined variable of change such as one upand/or one down), frequency modulation, amplitude modulation, musicprefix, music suffix and/or any other objective music attribute known inthe art. In various embodiments, biomarker identifier component 122 canextract the object qualities of the music through conversion to amathematical model and time function.

In various embodiments, biomarker identifier component 122 can sourcethe subjective music attributes through personal survey or crowdsourcedevaluation of the music. For example, a user loads/opens a musicapplication on a smartphone and begins listening to music using themusic application while on train. In this particular example, biomarkeridentifier component 122 triggers the monitoring the music choice andbiomarker identifier component 122 begins to extract the frequencyand/or amplitude of the music selected and/or played. In this particularexample, biomarker identifier component 122 models the qualities of themusic choices as a continuous function. Furthermore, in this particularexample, biomarker identifier component 122 compares the choices againsthistoric biomarkers as associated with prior health indicators, anddetermines the user's mood has dropped below a predetermined thresholdand alerts the user. In other embodiments, biomarker identifiercomponent 122 can alert the user, a healthcare professional, and/or anyother authorized member.

In various embodiments, biomarker identifier component 122 can monitorand/or record user music choices. In various embodiments, biomarkeridentifier component 122 can monitor music choices utilizing a shim,which intercepts the audio, records the music title, artist, start time,and end time (and fingerprint of the music), and captures a continuousfeed of the background audio. In other embodiments, biomarker identifiercomponent 122 can monitor and/or record user music choices by alsocapturing a user's location/region, user's age, user's gender, musicplayed with satisfaction, time window, and action/response to the music(e.g., fast-forwarding, skipping, repeating, etc.).

FIG. 2 is a flowchart depiction operational steps of biomarkeridentifier component 122, generally designated 200, on server computer120 within distributed data processing environment 100 of FIG. 1,monitoring biometric and biomarker data, in accordance with anembodiment of the present invention. FIG. 2 provides only anillustration of one implementation and does not imply any limitationswith regard to the environments in which different embodiments may beimplemented. Many modifications to the depicted environment may be madeby those skilled in the art without departing from the scope of theinvention as recited by the claims.

In step 202, biomarker identifier component 122 receives a user'scurrent audio preferences. In various embodiments, biomarker identifiercomponent 122 can receive one or more user preferences from a musicapplication (e.g., mobile music application). In various embodiments,biomarker identifier component 122 can receive a user's audiopreferences in real-time.

In step 204, biomarker identifier component 122 retrieves a user'shistoric audio preferences and biometric data. In various embodiments,biomarker identifier component 122 can retrieve a user's historic audiopreferences, historic biometric data, and/or real-time biometric datafrom local storage 108 and/or shared storage 124.

In step 206, biomarker identifier component 122 analyzes the user'scurrent audio preferences. In various embodiments, biomarker identifiercomponent 122 can analyze the user's current audio preferences andcompare them against the user's historic audio preferences, historicbiometric data, and current biometric data. In various embodiments,biomarker identifier component 122 can determine how audio preferencesaffects a user's biometric data and/or biomarker data and viscera.

In step 208, biomarker identifier component 122 creates a user biometricprofile. In various embodiments, biomarker identifier component 122creates a user biometric profile based on current audio preferences,historic audio preferences, current biometric data, and/or historicbiometric data.

In step 210, biomarker identifier component 122 outputs a user biometricprofile. In various embodiments, biomarker identifier component 122outputs a user biometric profile based on the analysis of historic andcurrent biometric data and/or audio preferences.

FIG. 3 is a flowchart depiction operational steps of biomarkeridentifier component 122, generally designated 300, on server computer120 within distributed data processing environment 100 of FIG. 1,monitoring biometric and biomarker data, in accordance with anembodiment of the present invention. FIG. 3 provides only anillustration of one implementation and does not imply any limitationswith regard to the environments in which different embodiments may beimplemented. Many modifications to the depicted environment may be madeby those skilled in the art without departing from the scope of theinvention as recited by the claims.

In step 302, biomarker identifier component 122 monitors a user's musicchoice. In various embodiments, biomarker identifier component 122monitors a user's music choice and/or audio preferences. In variousembodiments, biomarker identifier component 122 can retrieve and/ormonitor a user's music choice and/or audio preferences from the user'sbiometric profile.

In step 304, biomarker identifier component 122 extracts the musicfrequency and amplitude. In various embodiments, biomarker identifiercomponent 122 can extract the music frequency and amplitude from theuser's biometric profile and/or current music choice.

In step 306, biomarker identifier component 122 models the musicattributes. In various embodiments, biomarker identifier component 122can generate one or more models based on audio preferences, subjectivemusic attributes and/or objective attributes.

In step 308, biomarker identifier component 122 analyzes music choice.In various embodiments, biomarker identifier component 122 can analyze auser's music choice, extracted music frequency and amplitude, the one ormore models, historic biometric data, current biometric data, historicaudio preferences, current audio preferences, and/or user music choice.In various embodiments, biomarker identifier component 122 canaccumulate a score over a predetermined time period.

In step 310, biomarker identifier component 122 determines if the user'smood drops below a predetermined threshold. In various embodiments,biomarker identifier component 122 can determine if the user's mooddrops below a predetermined threshold based on the analysis in step 308.In this particular embodiment, if biomarker identifier component 122determines the user's mood drops below the predetermined threshold (Yesbranch) then biomarker identifier component 122 will advance to step312; however, if biomarker identifier component 122 determines that theusers mood hasn't dropped below the predetermined threshold (No branch),then biomarker identifier component 122 will repeat steps 302 through310 until biomarker identifier component 122 determines the user's mooddrops below the predetermined threshold. In various embodiments, thepredetermined threshold can be incremental, wherein the predeterminedthreshold includes levels/varying degrees of intensity and/orseriousness and/or warning thresholds.

In step 312, biomarker identifier component 122 alerts the user. Invarious embodiments, responsive to determining if the user's mood dropsbelow the predetermined threshold, biomarker identifier component 122can alert the user of the user's change in biomarker indicators/mood. Invarious embodiments, the alerts can be incremental starting with warningalerts if the user approaches the predetermined threshold within apredetermine buffer zone and the alerts intensify as the usersaccumulate score reaches closer to the threshold.

FIG. 4 depicts a block diagram of components of server computer 120within distributed data processing environment 100 of FIG. 1, inaccordance with an embodiment of the present invention. It should beappreciated that FIG. 4 provides only an illustration of oneimplementation and does not imply any limitations with regard to theenvironments in which different embodiments can be implemented. Manymodifications to the depicted environment can be made.

FIG. 4 depicts a block diagram of components of a computing devicewithin distributed data processing environment 100 of FIG. 1, inaccordance with an embodiment of the present invention. It should beappreciated that FIG. 4 provides only an illustration of oneimplementation and does not imply any limitations with regard to theenvironments in which different embodiments can be implemented. Manymodifications to the depicted environment can be made.

FIG. 4 depicts computer system 400, where server computer 120 representsan example of computer system 400 that includes biomarker identifiercomponent 122. The computer system includes processors 401, cache 403,memory 402, persistent storage 405, communications unit 407,input/output (I/O) interface(s) 406 and communications fabric 404.Communications fabric 404 provides communications between cache 403,memory 402, persistent storage 405, communications unit 407, andinput/output (I/O) interface(s) 406. Communications fabric 404 can beimplemented with any architecture designed for passing data and/orcontrol information between processors (such as microprocessors,communications and network processors, etc.), system memory, peripheraldevices, and any other hardware components within a system. For example,communications fabric 404 can be implemented with one or more buses or acrossbar switch.

Memory 402 and persistent storage 405 are computer readable storagemedia. In this embodiment, memory 402 includes random access memory(RAM). In general, memory 402 can include any suitable volatile ornon-volatile computer readable storage media. Cache 403 is a fast memorythat enhances the performance of processors 401 by holding recentlyaccessed data, and data near recently accessed data, from memory 402.

Program instructions and data used to practice embodiments of thepresent invention may be stored in persistent storage 405 and in memory402 for execution by one or more of the respective processors 401 viacache 403. In an embodiment, persistent storage 405 includes a magnetichard disk drive. Alternatively, or in addition to a magnetic hard diskdrive, persistent storage 405 can include a solid state hard drive, asemiconductor storage device, read-only memory (ROM), erasableprogrammable read-only memory (EPROM), flash memory, or any othercomputer readable storage media that is capable of storing programinstructions or digital information.

The media used by persistent storage 405 may also be removable. Forexample, a removable hard drive may be used for persistent storage 405.Other examples include optical and magnetic disks, thumb drives, andsmart cards that are inserted into a drive for transfer onto anothercomputer readable storage medium that is also part of persistent storage405.

Communications unit 407, in these examples, provides for communicationswith other data processing systems or devices. In these examples,communications unit 407 includes one or more network interface cards.Communications unit 407 may provide communications through the use ofeither or both physical and wireless communications links. Programinstructions and data used to practice embodiments of the presentinvention may be downloaded to persistent storage 405 throughcommunications unit 407.

I/O interface(s) 406 enables for input and output of data with otherdevices that may be connected to each computer system. For example, I/Ointerface 406 may provide a connection to external devices 408 such as akeyboard, keypad, a touch screen, and/or some other suitable inputdevice. External devices 408 can also include portable computer readablestorage media such as, for example, thumb drives, portable optical ormagnetic disks, and memory cards. Software and data used to practiceembodiments of the present invention can be stored on such portablecomputer readable storage media and can be loaded onto persistentstorage 405 via I/O interface(s) 406. I/O interface(s) 406 also connectto display 409.

Display 409 provides a mechanism to display data to a user and may be,for example, a computer monitor.

What is claimed is:
 1. A method for detecting user biomarker identifierchanges based on audio preferences and generating biometric alerts basedon the detected user biomarker identifier changes, the methodcomprising: receiving, by one or more processors, a user's current audiopreferences; retrieving, by the one or more processors, the user'shistoric audio preferences and biometric data associated with the user'shistoric audio preferences; analyzing, by the one or more processors,the user's current audio preferences based on the user's historic audiopreferences and the biometric data associated with the historic audiopreferences; creating, by the one or more processors, a user biometricprofile based on analyzing the user's current audio preferences, theuser's historic audio preferences and the biometric data associated withthe user's historic audio preferences; and outputting, by the one ormore processors, the user biometric profile.
 2. The method of claim 1,wherein analyzing the user's current audio preferences furthercomprises: parsing, by the one or more processors, the user's currentaudio preferences into subjective music attributes and objective musicattributes.
 3. The method of claim 1, wherein the user's current audiopreferences are divided into time segments of a predetermined interval.4. The method of claim 1, further comprising: alerting, by the one ormore processors, health professionals associated with the user based onthe biometric profile.
 5. The method of claim 1, wherein the user'scurrent audio preferences comprise at least one of: genre, music artist,lyrics, volume music is played, frequency of songs played, customplaylists, saved songs, liked songs, disliked songs, songs skipped, orbackground audio.
 6. The method of claim 2, wherein subjective musicattributes comprise at least one of: tonal character, noisy, with orwithout some tonal character, including rustle noise, coloration,beginning, ending, coloration glide or formant glide, micro-intonation,microtonality, vibrato, tremolo, attack, or final sound.
 7. The methodof claim 2, wherein objective music attributes comprise at least one of:periodic sound, noise, spectral envelope, physical rise and decay time,change of spectral envelope, change in frequency, frequency modulation,amplitude modulation, music prefix, or music suffix.
 8. A computerprogram product for detecting user biomarker identifier changes based onaudio preferences and generating biometric alerts based on the userdetected biomarker identifier changes, the method comprising: one ormore computer readable storage devices and program instructions storedon the one or more computer readable storage devices, the stored programinstructions comprising: program instructions to receive a user'scurrent audio preferences; program instructions to retrieve the user'shistoric audio preferences and biometric data associated with the user'shistoric audio preferences; program instructions to analyze the user'scurrent audio preferences based on the user's historic audio preferencesand the biometric data associated with the historic audio preferences;program instructions to create a user biometric profile based onanalyzing the user's current audio preferences, the user's historicaudio preferences and the biometric data associated with the user'shistoric audio preferences; and program instructions to output the userbiometric profile.
 9. The computer program of claim 8, wherein analyzingthe user's current audio preferences further comprises: programinstructions to parsing, by the one or more processors, the user'scurrent audio preferences into subjective music attributes and objectivemusic attributes.
 10. The computer program of claim 8, wherein theuser's current audio preferences are divided into time segments of apredetermined interval.
 11. The computer program of claim 8, furthercomprising: program instructions to alert health professionalsassociated with the user based on the biometric profile.
 12. Thecomputer program of claim 8, wherein the user's current audiopreferences comprise at least one of: genre, music artist, lyrics,volume music is played, frequency of songs played, custom playlists,saved songs, liked songs, disliked songs, songs skipped, or backgroundaudio.
 13. The computer program of claim 9, wherein subjective musicattributes comprise at least one of: tonal character, noisy, with orwithout some tonal character, including rustle noise, coloration,beginning, ending, coloration glide or formant glide, micro-intonation,microtonality, vibrato, tremolo, attack, or final sound.
 14. Thecomputer program of claim 9, wherein objective music attributes compriseat least one of: periodic sound, noise, spectral envelope, physical riseand decay time, change of spectral envelope, change in frequency,frequency modulation, amplitude modulation, music prefix, or musicsuffix.
 15. A computer system for detecting user biomarker identifierchanges based on audio preferences and generating biometric alerts basedon the user detected biomarker identifier changes, the computer systemcomprising: one or more computer processors; one or more computerreadable storage devices; program instructions stored on the one or morecomputer readable storage devices for execution by at least one of theone or more computer processors, the stored program instructionscomprising: program instructions to receive a user's current audiopreferences; program instructions to retrieve the user's historic audiopreferences and biometric data associated with the user's historic audiopreferences; program instructions to analyze the user's current audiopreferences based on the user's historic audio preferences and thebiometric data associated with the historic audio preferences; programinstructions to create a user biometric profile based on analyzing theuser's current audio preferences, the user's historic audio preferencesand the biometric data associated with the user's historic audiopreferences; and program instructions to output the user biometricprofile.
 16. The computer system of claim 15, wherein analyzing theuser's current audio preferences further comprises: program instructionsto parsing, by the one or more processors, the user's current audiopreferences into subjective music attributes and objective musicattributes.
 17. The computer system of claim 15, wherein the user'scurrent audio preferences are divided into time segments of apredetermined interval.
 18. The computer system of claim 15, furthercomprising: program instructions to alert health professionalsassociated with the user based on the biometric profile.
 19. Thecomputer system of claim 15, wherein the user's current audiopreferences comprise at least one of: genre, music artist, lyrics,volume music is played, frequency of songs played, custom playlists,saved songs, liked songs, disliked songs, songs skipped, or backgroundaudio.
 20. The computer system of claim 16, wherein subjective musicattributes comprise at least one of: tonal character, noisy, with orwithout some tonal character, including rustle noise, coloration,beginning, ending, coloration glide or formant glide, micro-intonation,microtonality, vibrato, tremolo, attack, or final sound; and whereinobjective music attributes comprise at least one of: periodic sound,noise, spectral envelope, physical rise and decay time, change ofspectral envelope, change in frequency, frequency modulation, amplitudemodulation, music prefix, or music suffix.